2 citations · 3 across the 5 of their papers we have counts for
5 papers
Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack
Ningfei Wang, Yunpeng Luo, Takami Sato +2
In autonomous driving (AD), accurate perception is indispensable to achieving safe and secure driving. Due to its safety-criticality, the security of AD perception has been widely…
Lateral-Direction Localization Attack in High-Level Autonomous Driving: Domain-Specific Defense Opportunity via Lane Detection
Junjie Shen, Yunpeng Luo, Ziwen Wan +1
Localization in high-level Autonomous Driving (AD) systems is highly security critical. While the popular Multi-Sensor Fusion (MSF) based design can be more robust against single-s…
On Gorenstein homological dimension of groups
Yuxiang Luo, Wei Ren
Let be a group and be a ring. We define the Gorenstein homological dimension of over , denoted by , as the Gorenstein flat dimension of trivial -…
MIRA: Leveraging Multi-Intention Co-click Information in Web-scale Document Retrieval using Deep Neural Networks
Yusi Zhang, Chuanjie Liu, Angen Luo +6
We study the problem of deep recall model in industrial web search, which is, given a user query, retrieve hundreds of most relevance documents from billions of candidates. The com…
GLOW : Global Weighted Self-Attention Network for Web Search
Xuan Shan, Chuanjie Liu, Yiqian Xia +6
Deep matching models aim to facilitate search engines retrieving more relevant documents by mapping queries and documents into semantic vectors in the first-stage retrieval. When l…